Dr. Ihab Hijazi is a researcher at the Chair of Geoinformatics , Technical University of Munich, specializing in 3D geospatial modeling and BIM-GIS integration . He teaches courses such as CAFM - Facility Management and GIS and contributes to advancing CityGML standards and urban digital twins . Research Focus : Hijazi’s work bridges Building Information Modeling (BIM) and Geographic Information Systems (GIS) , emphasizing interoperability , semantic transformation , and smart city infrastructures . His projects include the Smart Sustainable Districts (SSD) and Smart District Data Infrastructure , focusing on urban energy systems and data harmonization. Publications highlight his contributions to CityGML utility networks , urban growth simulations , and semantic modeling frameworks. He actively develops 3DCityDB and participates in standardization initiatives like the DIN Spec 91607 Digital Twin for Cities .
Professor Jing Meng is a leading academic at University College London's Bartlett School of Sustainable Construction, holding the position since 2023 after progressing from Lecturer (2019-2021) to Associate Professor (2021-2023). She concurrently serves as a fellow at the Cambridge Centre for Environment, Energy and Natural Resource Governance and maintains active editorial roles as Executive Editor of the Journal of Cleaner Production and Associate Editor for Journal of Geophysical Research: Atmospheres. Her research spans three interconnected domains: Energy Transitions and Technology Innovation (examining cost forecasts and structural emission declines in China), Climate Change Policies (analyzing South-South trade effects and multinational enterprise emissions), and Emission-Health-Socioeconomics Nexus (assessing air pollution impacts and integrated co-mitigation strategies). This interdisciplinary approach is reflected in her publication record across Nature family journals and PNAS. Analysis of her recent publications reveals a consistent focus on global carbon accounting methodologies, with increasing attention to subnational (city-level) analyses, health co-benefits of climate policies, and technological innovation pathways for hard-to-abate sectors. Her work frequently employs multi-regional input-output modeling to trace emissions through complex supply chains. AGU Global Environmental Change Early Career Award (2023) MIT Technology Review Innovators Under 35 Asia Pacific (2022) Clarivate Highly Cited Researcher (2020-2024) Nature Communications Top 50 Earth Sciences Article (2018) MDPI Emerging Sustainability Leader Award (2020) Environmental Research Letters Best Early Career Article (2017) Professor Meng has secured substantial funding from diverse sources including NERC, the British Council, Quadrature Climate Foundation, The Royal Society, and UCL internal grants. She leads an interdisciplinary research group focused on technology innovation and climate policy, with particular emphasis on China's role in global emissions systems. Her work directly supports Sustainable Development Goal 13 (Climate Action) through actionable policy insights.
Dr. Ken Ferens is an Assistant Professor in the Department of Electrical and Computer Engineering at the Price Faculty of Engineering, University of Manitoba. He serves as the Computer Engineering Champion in the Centre for Engineering Professional Practice and Engineering Education and directs the Applied Cognitive Intelligence (ACI) Research Group. Dr. Ferens is a senior member of the Institute of Electrical & Electronics Engineers (IEEE), Chair of the EduManCom Chapter of the IEEE, Vice-Chair of the Computer and Computational Intelligence Chapter of the IEEE, and Chair of the Industry, Teaching Assistants, and Student Forums for Engineering Curriculum Review and Improvement. Ph.D. (Computer Engineering), University of Manitoba, 1996 M.Sc. (Computer Engineering), University of Manitoba, 1991 B.Sc. (Electrical Engineering), University of Manitoba, 1989 Dr. Ferens has over 33 years of research experience in computational intelligence, focusing on cognitive machine learning, artificial intelligence, cognitive computational intelligence, chaos theory applications, agent-based models, and various optimization algorithms including simulated annealing, genetic algorithms, artificial neural networks, and particle swarm optimization. His research applies these techniques to develop software and hardware intrusion detection systems for cybersecurity applications. He teaches graduate-level courses on Computer Network Security and Applied Computational Intelligence, providing students with theoretical background and hands-on experience in state-of-the-art security methods. Analysis of Dr. Ferens' recent publications reveals a strong focus on applying cognitive and chaotic computational techniques to cybersecurity challenges, particularly malware detection and network intrusion detection. His work increasingly integrates complexity theory, fractal analysis, and hybrid optimization approaches to enhance security systems' effectiveness. There's a clear progression toward more sophisticated machine learning architectures applied to increasingly complex security scenarios, with growing emphasis on real-world IoT and network security applications. Best Paper Award at IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 2022) Best Paper Award at IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 2015) Best Journal Paper Award for 2013 (Journal of ICT Research and Applications) Best Poster Award at 12th International Conference on e-Health Networking, Application & Services (2010) Best Paper Award at IASTED International Conference on Computer, Electronics, Control, and Communication (1991) Dr. Ferens collaborates with national and international industry partners including the Department of Advanced Information Management, Content Technology Canadian Tire Corporation (CTC), and Magellan Aerospace. His research group has received funding supporting the Cyber-security Research Program, developing practical applications of computational intelligence for security systems. He has supervised numerous graduate students in the Electrical and Computer Engineering department, focusing on research at the intersection of machine learning and cybersecurity. Dr. Ferens leads the Applied Cognitive Intelligence (ACI) Research Group within the Department of Electrical and Computer Engineering, which focuses on applying cognitive, chaotic, and computationally intelligent algorithms to build intrusion detection systems. The group collaborates with industry partners to develop practical security solutions while providing students with hands-on research experience in cutting-edge security technologies. Their work spans both theoretical algorithm development and practical hardware implementation for real-world security applications.
James S. Noble is a Professor and Chair of the Department of Industrial and Systems Engineering at the University of Missouri, where he also serves as the MU Site Director for the NSF I/UCRC Center for Excellence in Logistics and Distribution (CELDi). His work bridges academia and industry through applied research in logistics, supply chain, and integrated production systems. PhD, Purdue University MS, Purdue University BS, University of Oklahoma Dr. Noble's research focuses on logistics and distribution , supply chain system design , and integrated production systems , with applications ranging from humanitarian logistics to intelligent warehouse systems. His work emphasizes modeling, analysis, and optimization of material flow and transportation systems. The 15 most recent articles reflect a consistent trajectory in logistics systems analysis , supply chain modeling , and material flow improvement . These publications demonstrate a strong integration of operations research, systems engineering, and real-world problem-solving, with applications in energy, transportation, humanitarian aid, and industrial logistics. Keywords span Operations Research , Supply Chain Management , and Industrial Engineering , while sub-fields include Bayesian forecasting, reverse logistics, winter road maintenance, and intelligent systems. Dr. Noble has been recognized with several prestigious awards: Society of Manufacturing Engineers Outstanding Young Manufacturing Engineering Award (1997) William T. Kemper Fellowship for Teaching Excellence (2022) Win Horner Award for Innovative Writing Intensive Teaching (2014) Elected Fellow of the Institute for Industrial and Systems Engineering (IISE) (2019) His research has been generously funded by the National Science Foundation , Bayer , Boeing , Hallmark Cards , Honeywell FMT , Medline , Ameren , UMB Financial , the U.S. Economic Development Administration , the Midwest Transportation Consortium , and the Missouri Department of Transportation . While specific advisees are not listed, his leadership in CELDi and role as department chair suggest extensive mentorship of graduate and undergraduate students in real-world logistics projects. He is also a registered Professional Engineer in Missouri. As MU Site Director for CELDi, Dr. Noble leads a multidisciplinary team of faculty from Industrial Engineering, Civil Engineering, Geography, and Biological Engineering, collaborating with over 30 industry, military, and government partners to solve real-world logistics challenges and develop implementable, cutting-edge solutions.
Jordi Guitart Fernández is a Professor at the Department of Computer Architecture, Barcelona School of Informatics (FIB), Universitat Politècnica de Catalunya (UPC). He is also affiliated with the Barcelona Supercomputing Center (BSC-CNS), a leading national supercomputing facility. He leads the CROMAI research group, focusing on Computing Resources Orchestration and Management for AI. His work bridges high-performance computing, cloud systems, and artificial intelligence. Research Interests: Cloud Computing and Edge Computing Green and Energy-Efficient Computing Containerization and Virtualization for HPC Resource Orchestration and Management Autonomic and Self-Adaptive Systems Machine Learning Workflow Management AI-Driven System Optimization His recent publications reveal a strong focus on intelligent management of computing resources across cloud, edge, and HPC environments using machine learning and agent-based frameworks. He investigates performance, efficiency, and reliability in containerized AI and HPC workloads, particularly within Kubernetes and distributed infrastructures. His work increasingly integrates human-in-the-loop and trustworthiness aspects into AI systems. Scientific Awards: CLOUD Conference 2025 Best Paper Award VISIGRAPP 2025 Best Student Paper Award Premi Extraordinari de Doctorat 2025 - Àmbit d'Enginyeria de les TIC Test of Time Award Honorable Mention (e-Energy) Reconeixement als Mèrits Docents d'Especial Qualitat Top reviewers for Polytechnic University of Catalonia (Computer Science) - September 2017 Advising and Grants: He has advised doctoral students, including Peini Liu. He leads and participates in numerous competitive R+D+i projects, such as CROMAI and DALEST, funded by national and European programs like HORIZON 2020 and the Spanish State Research Plans. His work is supported by grants focused on knowledge generation and industrial leadership in computing technologies. Labs and Teams: He is the leader of the CROMAI - Computing Resources Orchestration and Management for AI research group at UPC. He also collaborates closely with the Barcelona Supercomputing Center (BSC-CNS), contributing to large-scale computing initiatives and strategic research agendas in Europe.
Dr. Yongchao Huang is a Lecturer (Assistant Professor) in the School of Natural and Computing Sciences at the University of Aberdeen, where he has been employed since August 2023. He also holds affiliations with the University of Oxford and the University of Cambridge through past postdoctoral and collaborative roles. He is actively involved in research, teaching, and academic service, and is currently accepting PhD students. His educational background includes: DPhil in Engineering Science, University of Oxford (2013–2017) Additional training in Machine Learning at Oxford (2015–2019) Dr. Huang's research focuses on fundamental and physics-informed machine learning, with core interests in Bayesian inference, variational methods, generative modeling (especially score-based), reinforcement learning, and interdisciplinary AI applications in mechanics, biology, energy, climate, and finance. A central theme of his work is the inference and sampling of probability densities, particularly through innovative particle-based and physics-inspired computational frameworks. He founded the Computational and Physical Learning (CPL) lab at Aberdeen in 2023. His recent publications (2020–2025) reflect a strong trend in probabilistic machine learning, with increasing focus on physics-based inference methods such as electrostatics, fluid dynamics, and material point methods. These works bridge machine learning with applied mathematics and physical simulation, demonstrating a unique interdisciplinary approach. Topics span Bayesian neural networks, acoustic wave propagation, mortality modeling, and adversarial cybersecurity. Dr. Huang has received academic recognition through invitations to serve on program committees and editorial roles: Program Committee Member, ECAI 2024 Organizing Committee, Bioinference 2024 Guest Editor, Journal of Theoretical Biology Senior Scientific Advisor to a UK firm He has supervised 57 MSc theses independently and currently supervises one PhD student. He has secured research engagement through collaborations with institutions including Oxford, Cambridge, and industry partners. His teaching includes courses such as Introduction to Software Engineering , Software Process and Management , and Computational Intelligence at Aberdeen, as well as practicals in inference at Cambridge. Dr. Huang leads the Computational and Physical Learning (CPL) lab at the University of Aberdeen, a curiosity-driven research group focused on foundational advances in machine intelligence. Though currently a solo researcher due to limited resources, the lab emphasizes end-to-end research and open collaboration. He encourages student mobility and interdisciplinary exploration.
Gustavo Vulcano is an Adjunct Professor in the Department of Information, Operations and Management Sciences at the Leonard N. Stern School of Business, New York University, where he has been affiliated since 2002. He served as Assistant Professor (2002–2010), Associate Professor (2010–2017, tenured in 2012), and has held an adjunct role since 2017. His academic work bridges theoretical and applied operations management with strong industry engagement. Education: Ph.D. in Operations Management, Columbia University, 2003 M.Phil. in Operations Management, Columbia University, 2000 M.S. in Computer Science, University of Buenos Aires, 1997 B.S. in Computer Science, University of Buenos Aires, 1994 His research focuses on revenue and pricing analytics , retail operations , and supply chain management , particularly emphasizing customer choice modeling , data-driven optimization , and computational methods in network revenue management . He integrates stochastic modeling and behavioral insights to develop practical pricing and operational strategies. His work is deeply rooted in real-world applications across airlines, retail, and financial services. The analysis of his publications reveals a consistent trend in leveraging data-driven decision-making under uncertainty, with a focus on dynamic pricing, demand learning, and robust optimization. His articles span premier journals such as Operations Research and Management Science , reflecting a strong theoretical foundation combined with empirical and computational rigor. Key thematic areas include customer behavior modeling, network revenue management, and stochastic optimization for service industries. Scientific Awards and Leadership: Chair, INFORMS Revenue Management and Pricing Section (2016–2017) Associate Editor, Operations Research and Management Science Prof. Vulcano has advised numerous PhD and master’s students and has secured research grants through industry collaborations. His consulting projects with Delta Airlines, Sabre Holdings, Aerolíneas Argentinas, and ICBC demonstrate a strong commitment to translating academic research into practical solutions. He has taught core courses such as Operations Management , Pricing and Revenue Management , and Dynamic Programming across undergraduate, MBA, PhD, and MSBA programs, shaping future leaders in data-driven decision-making. He is actively involved in research labs and teams focused on operations analytics and pricing strategy , often collaborating with interdisciplinary groups at NYU Stern and industry partners. His ongoing editorial roles and consultancy reflect sustained engagement in advancing the field of revenue management and operations science.
Isaac Gross is a Senior Lecturer in the Department of Economics at Monash University, Faculty of Business and Economics. He holds a PhD and is actively involved in research, teaching, and policy advisory roles. His work bridges academic theory and real-world economic policy, particularly in macroeconomic and monetary domains. His research interests center on macroeconomics , monetary policy , DSGE modeling , and commodity price dynamics . He employs advanced quantitative methods to analyze policy effectiveness and economic stability, with a regional focus on Australia and global commodity markets. The recent articles highlight a consistent focus on nonlinear modeling of macroeconomic systems, optimal policy design , and structural analysis of monetary and resource sectors . His work combines theoretical rigor with empirical validation, often using large-scale models like MARTIN for policy simulation. Scientific Awards: Best Paper at the Melbourne Institute Macroeconomic Policy Meeting (2018) Dean's Citations for Outstanding Contribution to Student Learning (2021) Advising and Grants: Isaac Gross served as the Primary Chief Investigator on the 2022 research project Estimating Optimal Policy Rules for Australian Monetary Policy with MARTIN . While formal student advising is not listed, his Dean’s Citation underscores significant contributions to student learning. He has also contributed to educational initiatives such as continuing education in macroeconometrics. Labs, Teams, and Collaborations: He collaborates with prominent economists including Andrew Leigh and J. Hansen. His work involves external engagement with key institutions such as the Reserve Bank of Australia and the Standing Committee on Economics, indicating integration into national policy networks.
Mingzhou Jin is a Professor and Department Head in the Department of Industrial and Systems Engineering at the University of Tennessee, Knoxville, within the Tickle College of Engineering. He also directs the Institute for a Secure and Sustainable Environment (ISSE) and the FERSC Center, a DOT/UTC Tier-1 Center. Holding the John D. Tickle Professorship, he is a recognized leader in sustainability, optimization, logistics, and smart manufacturing. PhD, Industrial and Systems Engineering, Lehigh University, 2001 MS, Management Science, Zhejiang University, 1998 BS, Electrical Engineering and Mixed Class, Zhejiang University, 1995 Dr. Jin's research focuses on sustainability, climate change, transportation and logistics, supply chain engineering, additive and smart manufacturing, and energy efficiency. His work integrates operations research and systems engineering to solve complex environmental and industrial challenges. He has secured over $19 million in research funding from agencies including NSF, DOE, DOT, DHS, and industry partners like FedEx, Boeing, and Schneider Electric. His recent publications span high-impact journals such as Nature , Nature Communications , and European Journal of Operational Research , with themes in net-zero strategies, wildfire modeling, smart manufacturing, and sustainable supply chains. The research demonstrates a strong trend toward interdisciplinary, data-driven solutions for global environmental and industrial systems. 2023 Dr. Kenneth Kirby Endowed Faculty Award 2021 UTK Award for Success in Multidisciplinary Research 2020 UTK Chancellor’s Research and Creative Achievement Award 2020 TCE Research Achievement Award IISE Fellow (2018) Multiple teaching, advising, and service awards from TCE and UTK Dr. Jin has advised numerous graduate students and led large-scale research initiatives. He has served as Editor-in-Chief of Cleaner and Circular Bioeconomy , Executive Editor of Journal of Cleaner Production , and held leadership roles in IISE. His research has been supported by extensive grants from federal agencies and industry, reflecting strong collaboration and real-world impact. He also held adjunct professorships at Zhejiang University and Central South University of Forestry and Technology. He leads the Institute for a Secure and Sustainable Environment (ISSE) and the FERSC Center, fostering interdisciplinary research in sustainability, energy, and resilient infrastructure. These centers bring together experts from engineering, environmental science, and policy to address pressing global challenges through systems-level innovation.
Jonn Axsen is a Professor in the School of Resource & Environmental Management at Simon Fraser University (SFU), where he directs the Sustainable Transportation Research Team (START). With an academic career focused on mitigating transportation emissions, he bridges individual decision-making, social systems, technology, and public policy to advance sustainable mobility solutions. BBA, Business Administration (First Class Honours), Simon Fraser University MRM, Resource Management, Simon Fraser University PhD, Transportation Technology and Policy, University of California, Davis His research identifies solutions for decarbonizing road transportation, examining electric vehicles, alternative mobility systems, and policy frameworks. He emphasizes interdisciplinary approaches to understand consumer behavior, organizational transitions, and policy effectiveness in achieving zero-emissions vehicle adoption. Recent publications focus on policy mixes for ZEV adoption, automobility reduction, and consumer perceptions of emerging mobility technologies. Key trends include analyzing subsidy effectiveness, automaker responses to regulation, and cross-cultural differences in mobility preferences. His work appears in top venues like Nature Climate Change and Transportation Research Part D . Royal Society of Canada Fellow (2021) International Transport Forum Award (2012) Securing $2M+ in grants from SSHRC, Translink, Tesla, and PICS, Axsen collaborates with organizations including the UN, Transport Canada, and environmental NGOs. He serves as Senior Associate Editor for Energy Research & Social Science and sits on the US National Academies’ Transportation Research Board. The START team at SFU conducts applied research on sustainable transportation, integrating stakeholder insights with academic rigor. Axsen's lab focuses on bridging technical and social dimensions of mobility transitions through mixed-method studies.
Kash Barker serves as the John A. Myers Professor and David L. Boren Professor at the University of Oklahoma in the Department of Industrial & Systems Engineering within the College of Engineering. As Graduate Liaison, he leads research on network resilience, supply chains, and systems engineering for societal good, with applications spanning infrastructure, supply chains, and community systems. His lab has produced 11 Ph.D. graduates (10 in academia) and 31 M.S. graduates. Research Domains: Resilient networks and interdependent systems Risk and decision analytics Supply chain survivability Pandemic economic impact modeling Climate migration optimization Cyber-Physical-Social Systems Article Trends emphasize disinformation defense , network restoration optimization , and multi-layer resilience modeling across infrastructure, supply chains, and community systems. His work combines game theory , machine learning , and decision analysis frameworks. Scientific Awards & Roles: Fellow, Institute of Industrial and Systems Engineers Senior Member, IEEE Fellow, Fulbright Finland Foundation (2023) Associate Editor roles in IISE Transactions and Naval Research Logistics Editorial Board Member for Risk Analysis and Scientific Reports Faculty Advisor, OU INFORMS student chapter Educational Background: Ph.D., Systems Engineering, University of Virginia M.S., Industrial Engineering, University of Oklahoma B.S., Industrial Engineering, University of Oklahoma
Eunchun Park serves as an Assistant Professor in the Department of Agricultural Economics and Agribusiness at the University of Arkansas, concurrently holding the position of Director of the Experiment Station (DREX). A specialist in Bayesian spatial statistics and econometrics, his research focuses on agricultural risk analysis with particular emphasis on crop insurance mechanisms and financial commodity markets. His methodological expertise addresses critical data scarcity challenges in federal crop insurance premium calculations through advanced spatial modeling techniques. Dr. Park's academic foundation includes: Ph.D. in Agricultural Economics from Oklahoma State University (2017) M.S. in Food and Resource Economics from Korea University (2013) B.S. in Food and Resource Economics from Korea University (2010) His research program centers on extreme price and yield risk quantification in agricultural commodities, employing sophisticated Bayesian modeling frameworks to overcome data limitations in spatial risk assessment. Current work develops innovative approaches for measuring catastrophic risks in crop production systems and refining insurance rating structures through spatial smoothing of yield densities. This research bridges theoretical econometric advances with practical applications for risk management tools used by farmers and policymakers. Analysis of Dr. Park's recent publications reveals a consistent trajectory in spatial risk modeling for agricultural insurance systems, with increasing focus on prevented planting coverage factors, commodity market volatility around information releases, and climate-related production risks. His work demonstrates methodological progression from theoretical Bayesian frameworks toward actionable risk assessment tools, particularly through the application of kriging techniques to non-normal yield distributions and extreme event modeling. Dr. Park's scholarly contributions have been recognized through: Outstanding Contribution to Applied Risk Analysis Award (2020) from the Agricultural and Applied Economics Association Outstanding Graduate Student Paper Award (2018) from the Agricultural and Applied Economics Association Outstanding Doctoral Dissertation Award (2018) from the Southern Agricultural Economics Association While specific details of current advisees and grant funding are not provided in available materials, his active publication record in top agricultural economics journals suggests an ongoing mentorship role for graduate students and potential involvement in externally funded research initiatives related to agricultural risk management. His work on spatial smoothing techniques and extreme risk modeling likely informs collaborative projects with agricultural extension services and federal risk management agencies. No specific laboratory facilities or dedicated research teams are mentioned in the available documentation, though his methodological expertise suggests collaboration with spatial statistics and agricultural risk modeling groups within the university's research infrastructure.
Maxwell Young is an Associate Professor in the Department of Computer Science and Engineering at Mississippi State University's College of Engineering. His office is located in 312 Butler Hall and he can be reached at myoung@cse.msstate.edu. Previously, he served as an Assistant Professor at Drexel University in Philadelphia, following postdoctoral positions at the University of Michigan (working with Seth Pettie) and the National University of Singapore (working with Seth Gilbert). Young earned his PhD from the University of Waterloo, Canada, under the supervision of Raouf Boutaba and Martin Karsten, his MS from the University of New Mexico under Jared Saia, and his BS in mathematics from Queen's University, Canada. His research focuses on the design and analysis of algorithms for decentralized networks that yield provable guarantees with respect to security, fault tolerance, and performance. His primary research areas include distributed computing, computer security, and theoretical algorithms, with specific emphasis on contention resolution protocols, Sybil attack defenses, and resource-competitive approaches to network security. His work bridges theoretical computer science with practical applications in wireless networks and distributed systems. Analysis of his recent publications reveals a consistent trajectory focused on making distributed systems more resilient against adversarial attacks while optimizing resource usage. His research demonstrates sophisticated application of probabilistic analysis and algorithmic game theory to security challenges, with particular innovation in creating asymmetric defenses where attackers must expend disproportionate resources compared to legitimate users. Best Paper Award at SIROCCO 2025 for 'Bankrupting DoS Attackers' Best Paper Award at SSS 2024 for 'Softening the Impact of Collisions in Contention Resolution' Best Paper Award at ICDCN 2024 for 'Defending Hash Tables from Subterfuge with Depth Charge' Young has received significant research funding through grants including 'Collaborative Research: SaTC: CORE: Small: Bankrupting Attackers in Dynamic Networks' and 'CAREER: Make Them Pay! Algorithms for Securing Wireless Systems.' His work on resource-competitive algorithms provides theoretical foundations for designing systems where adversaries must spend significantly more resources than legitimate users to mount successful attacks. His research group appears to focus on distributed algorithms and network security, with particular attention to practical implementations of theoretically sound approaches. Young has collaborated extensively with researchers including Jared Saia, Seth Gilbert, and Diksha Gupta on security-related algorithmic challenges.
Professor Zoran A. Ristić serves as Head of Department at the Department of Geography, Tourism and Hotel Management, Faculty of Natural Sciences and Mathematics, University of Novi Sad. With over 40 years of academic and professional engagement in wildlife management, he has established himself as Serbia's leading expert in hunting science and game biology. His research interests focus on Wildlife Management , Game Biology , and Hunting Tourism , with particular expertise in population dynamics of game species, hunting ground management, and sustainable utilization of wildlife resources. His work bridges academic research with practical applications through extensive collaboration with hunting associations across Serbia, Republika Srpska, and Croatia. Analysis of his recent publications reveals a strong trend toward integrating ecological monitoring with management practices , particularly in roe deer population genetics, habitat assessment using remote sensing, and disease surveillance in wildlife. His work consistently addresses practical challenges in game management while advancing methodological approaches. Silver Order of the Hunting Association of Yugoslavia (1986) Gold Order of the Hunting Association of Serbia (1995) University of Novi Sad Plaque for Best Rated Professor (2008-2013) Over 40 hunting association awards and diplomas Professor Ristić has mentored 1 doctoral student, 3 master's students, 15 specialist students, and 105 diploma students. His extensive grant portfolio includes leadership roles in over 15 major research projects funded by the Provincial Secretariat for Science, Ministry of Agriculture, and hunting associations, focusing on game population dynamics, habitat management, and wildlife health monitoring. He directs the Hunting Breeding, Protection and Scientific Research Commission of the Hunting Association of Vojvodina and serves on multiple editorial boards for hunting publications.
Alberto Rodrigues da Silva is a Professor at the Institute Superior Técnico , part of the University of Lisbon . He teaches Fundamentals of Information Systems , primarily during the 1st Semester of the 2025/2026 academic year. His scientific interests revolve around Information Systems , Model-Driven Engineering (MDE), Requirements Engineering (RE), Social Computing , and Software Engineering . He has extensively contributed to the development of rigorous requirements specification languages like RSL (Requirements Specification Language) and its extensions (e.g., RSL-IL4Privacy for privacy policies). His collaborative work spans automated acceptance testing, GDPR compliance, and domain-specific languages (DSLs) for applications such as mobile development , digital twins , and legal contexts (e.g., LegalLanguage ). His research trends focus on integrating model-driven engineering with privacy policies , IoT applications , and low-code platforms . He has also explored tools like Maestro for data classification and usability testing, and RiverCure for flood simulation. Email: alberto.silva@tecnico.ulisboa.pt .
